What question did this study set out to answer?

The aim is to explore the advancements and applications of spatial transcriptomics in understanding cardiac homeostasis and injury.

June 24, 2026Open Access

Decoding cardiac homeostasis and injury: the evolving landscape of spatial transcriptomics

Q: What is the clinical evidence from this study?

Study design: Review. Population: Cardiac homeostasis and injury. Intervention: Spatial transcriptomics.

AHAnis HannaAlbert Einstein College of Medicine

Key Result

Spatial transcriptomics technologies, including sequencing- and imaging-based methods, enable high-resolution mapping of gene expression to histological coordinates in the healthy and injured heart.

Key Points

The aim is to explore the advancements and applications of spatial transcriptomics in understanding cardiac homeostasis and injury.
Review of spatial transcriptomics technologies including sequencing-based (e.g., Visium, Stereo-seq) and imaging-based methods (e.g., MERFISH, Xenium, CosMx).
Discussion of applications of spatial techniques in mapping heart architecture during homeostasis and injury.
Exploration of future directions in spatial multi-omics, including proteomic profiling and chromatin analysis.
Spatial transcriptomics bridges the gap left by single-cell RNA sequencing by retaining spatial context.
Technologies like seq-IF and iPEX enhance our understanding of the heart's molecular landscape post-injury.
Integration of multi-modal datasets poses computational challenges but promises comprehensive atlases of cardiac function.

PICO

Population

Cardiac homeostasis and injury

Intervention / Comparator

Spatial transcriptomics

Limitations

Sequencing-based methods are limited by capture efficiency, leading to gene dropout and data sparsity.
Lateral diffusion of mRNA during permeabilization can cause signal bleed-through.
Accurate cell segmentation remains a computational challenge.
Imaging-based methods face optical crowding in regions of high transcript density.
Reliance on external atlases for spatial transcriptomics deconvolution can introduce biases.

Abstract

The heart is a structurally complex organ where function is intimately tied to the precise spatial organization of diverse cell types. While single-cell RNA sequencing (scRNA-seq) has revolutionized cardiovascular research by providing a high-resolution "parts list" of the heart, the requisite tissue dissociation destroys the critical spatial context of intercellular communication and microenvironmental niches. Spatial transcriptomics (ST) has emerged as a transformative technology that bridges this gap, enabling the mapping of gene expression back to its histological coordinates. This review discusses the rapidly evolving landscape of spatial technologies, categorizing them into sequencing-based methods (e.g., Visium, Stereo-seq) which offer transcriptome-wide discovery, and imaging-based methods (e.g., MERFISH, Xenium, CosMx) which provide subcellular resolution with high sensitivity. We highlight recent applications of these tools in uncovering the spatial architecture of the heart at homeostasis and following injury. Furthermore, we explore the next frontier of spatial multi-omics, including simultaneous profiling of the proteome via sequential immunofluorescence (seq-IF) and expansion proteomics (iPEX), as well as chromatin accessibility. We conclude by discussing the computational challenges and future perspectives of integrating these multi-modal datasets to construct comprehensive atlases of the healthy and injured heart.

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